limkokhole

#!/usr/bin/env python
"""Compare two aligned images of the same size.

Usage: python compare.py first-image second-image
"""

import sys

from scipy.misc import imread
from scipy.linalg import norm

limkokhole

/***********************************************************************
 * connect.c -- Make socket connection using SOCKS4/5 and HTTP tunnel.
 *
 * Copyright (c) 2000-2004 Shun-ichi Goto
 * Copyright (c) 2002, J. Grant (English Corrections)
 *
 * This program is free software; you can redistribute it and/or
 * modify it under the terms of the GNU General Public License
 * as published by the Free Software Foundation; either version 2
 * of the License, or (at your option) any later version.

limkokhole

Detecting similar and identical images using perseptual hashes

Couple of my hobbies are travelling and photography. I love to take pictures and experiment with photography. Usually after my trips, I just copy the photos to either my iPad or couple of my external hard disks. After 10 years, I have over 200K photos distributed across several disks and machines. I had to find a way to organize these photos and create a workflow for future maintenance. In this post I want to address one of the issues I had to solve: ** finding duplicate images **.

First, I needed to find out what exactly is a duplicate image. Analysing my photos, I found couple of interesting things:

1. Identical images: There were multiple copies of the same photo in different directories with different names.
Similar images: I usually bracket (exposure compensate or flash compensate) important pictures. So I have photos that visually appear to be the same, but may be a little darker/lighter based on e

limkokhole

/* exec-notify, so you can watch your acrobat reader or vim executing "bash -c"
 * commands ;-)
 * Requires some 2.6.x Linux kernel with proc connector enabled.
 *
 * $  cc -Wall -ansi -pedantic -std=c99 exec-notify.c
 *
 * (C) 2007-2010 Sebastian Krahmer <krahmer@suse.de> original netlink handling
 * stolen from an proc-connector example, copyright folows:
 */
/*

limkokhole

curl --include \
     --no-buffer \
     --header "Connection: Upgrade" \
     --header "Upgrade: websocket" \
     --header "Host: example.com:80" \
     --header "Origin: http://example.com:80" \
     --header "Sec-WebSocket-Key: SGVsbG8sIHdvcmxkIQ==" \
     --header "Sec-WebSocket-Version: 13" \
     http://example.com:80/

limkokhole

#include <string>
#include "regex.h"


/*
 * Return a new string with all occurrences of 'from' replaced with 'to'
 */
std::string replace_all(const std::string &str, const char *from, const char *to)
{
    std::string result(str);

limkokhole

#!/usr/bin/env python
# requires
# Creates a requirements.txt file using pip freeze.
#
# Author:   Benjamin Bengfort <benjamin@bengfort.com>
# Created:  Fri Jan 22 08:50:31 2016 -0500
#
# Copyright (C) 2016 Bengfort.com
# For license information, see LICENSE.txt
#

limkokhole

## {{{ http://code.activestate.com/recipes/578019/ (r15)
#!/usr/bin/env python

"""
Bytes-to-human / human-to-bytes converter.
Based on: http://goo.gl/kTQMs
Working with Python 2.x and 3.x.

Author: Giampaolo Rodola' <g.rodola [AT] gmail [DOT] com>
License: MIT

limkokhole

import requests
import string
import random
import urllib
import time
import base64
from decimal import Decimal

# Blind GQL injection and optimised binary search - A7 ~ Gee cue elle (misc) Google CTF 2017 
# https://www.youtube.com/watch?v=za_9hrq-ZuA

limkokhole

from pwn import *

s = log.waitfor("Calculating CRC reverse lookup table")
reverse_crc = {crc.crc_32(p16(i)): p16(i) for i in range(2**16)}
s.success()

e = ELF("./crcme_8416479dcf3a74133080df4f454cd0f76ec9cc8d")
r = process("./crcme_8416479dcf3a74133080df4f454cd0f76ec9cc8d")

@MemLeak